Ordenação de eventos e interpretação de contextos em redes de atuadores e sensores sem fio para a classe de aplicações de preparação para emergência

Abstract

Wireless Sensor and Actor Networks (WSANs) are increasingly being deployed for fine-grain monitoring of physical environments subjected to emergency situations such as fire, leaking of toxic gases and explosions. In these environments a reliable interpretation of the collected events is very important. However, the order in which events are received can interfere directly with the correct interpretation of what is going on in the physical environment being monitored. Therefore, the ordering of events in WSAN can be a major requirement for critical security monitoring applications because by handling event ordering, ambiguities can be dealt with, increasing the accuracy of what is being monitored. This work describes a novel algorithm for event ordering in WSAN called OBC (Ordering by Confirmation). This low latency and energy aware protocol was discussed and evaluated against existing solutions, showing that it can save more energy and achieve lower latencies in situations where the network density, event rate and network dimension increase. This work also presents a context interpretation solution that can interpret from simple to complex contexts. In this solution, actors are used to aggregate sensor events, eliminate ambiguities and redundancy and realize context interpretations. Each actor of the WSAN is configured with rules that are determined by the application in the network configuration phase. After ordered, correlated events are interpreted resulting in contexts that go from simple questions, such as What is the temperature of sector A? to more complex ones Why did the aircraft wing crack? . Context information is exchanged among actors and sink(s) of the WSAN through the publish/subscribe technique based on topics. Our solution was compared to a centralized solution, in which events are collected by the sink. Results from simulations have shown that by having actors for decentralized context interpretation and a fast energy-aware event ordering algorithm, our solution can be a good alternative for emergency preparedness applications where lives and patrimony are at risk.